Added class colors to run_tf_detector

api/detector_batch_processing/find_problematic_detections.py

@@ -126,6 +126,8 @@ class SuspiciousDetectionResults:
 
     masterHtmlFile = None
 
+    filterFile = None
+
 
 class IndexedDetection:
     '''
@@ -852,6 +854,8 @@ def find_suspicious_detections(inputCsvFilename,outputCsvFilename,options=None):
     with open(detectionIndexFileName, 'w') as f:
         f.write(s)
 
+    toReturn.filterFile = detectionIndexFileName
+
     return toReturn
 
 # ...find_suspicious_detections()

api/detector_batch_processing/postprocess_batch_results.py

@@ -228,7 +228,12 @@ def render_bounding_boxes(image_base_dir,image_relative_path,
 
 
 def prepare_html_subpages(images_html,output_dir,options=None):
+    """
+    Write out a series of html image lists, e.g. the fp/tp/fn/tn pages.
     
+    image_html is a dictionary mapping an html page name (e.g. "fp") to a list
+    of image structs friendly to write_html_image_list
+    """
     if options is None:
             options = PostProcessingOptions()
 
@@ -499,11 +504,9 @@ def process_batch_results(options):
             else:
                 res = 'tn'
 
-            display_name = '<b>Result type</b>: {}, <b>Presence</b>: {}, <b>Class</b>: {}, <b>Image</b>: {}'.format(
-                res.upper(),
-                str(gt_presence),
-                gt_class_name,
-                image_relative_path)
+            display_name = '<b>Result type</b>: {}, <b>Presence</b>: {}, <b>Class</b>: {}, <b>Max conf</b>: {:0.2f}%, <b>Image</b>: {}'.format(
+                res.upper(), str(gt_presence), gt_class_name,
+                max_conf * 100, image_relative_path)
 
             rendered_image_html_info = render_bounding_boxes(options.image_base_dir,
                                                              image_relative_path,
@@ -530,8 +533,8 @@ def process_batch_results(options):
         <a href="tn.html">True negatives (tn)</a> ({})<br/>
         <a href="fp.html">False positives (fp)</a> ({})<br/>
         <a href="fn.html">False negatives (fn)</a> ({})<br/>
-        <br/><p>At a confidence threshold of {:0.1f}%, precision={:0.2f}, recall={:0.2f}</p>
-        <br/><p><strong>Precision/recall summary for all {} images</strong></p><img src="{}"><br/>
+        <p>At a confidence threshold of {:0.1f}%, precision={:0.2f}, recall={:0.2f}</p>
+        <p><strong>Precision/recall summary for all {} images</strong></p><img src="{}"><br/>
         </body></html>""".format(
             count, confidence_threshold * 100,
             image_counts['tp'], image_counts['tn'], image_counts['fp'], image_counts['fn'],

detection/detection_eval/load_api_results.py

@@ -54,7 +54,7 @@ def load_api_results(filename,normalize_paths=True,filename_replacements={}):
             fn = fn.replace(string_to_replace,replacement_string)
             detection_results.at[iRow,'image_path'] = fn
 
-    print('Finished loading and de-serializing API results from {}'.format(filename))    
+    print('Finished loading and de-serializing API results for {} images from {}'.format(len(detection_results),filename))    
 
     return detection_results
 

detection/run_tf_detector.py

@@ -8,9 +8,8 @@
 #
 # See the "test driver" cell for example invocation.
 #
-# It's clearly icky that if you give it blah.jpg, it writes the results to 
-# blah.detections.jpg, but I'm defending this with the "just a demo script"
-# argument.
+# If no output directory is specified, writes detections for c:\foo\bar.jpg to
+# c:\foo\bar_detections.jpg .
 #
 ######
 
@@ -37,6 +36,9 @@
 # Stick this into filenames before the extension for the rendered result
 DETECTION_FILENAME_INSERT = '_detections'
 
+BOX_COLORS = ['r','g','b']
+DEFAULT_LINE_WIDTH = 10
+
 
 #%% Core detection functions
 
@@ -197,7 +199,7 @@ def generate_detections(detection_graph,images):
 #%% Rendering functions
 
 def render_bounding_box(box, score, classLabel, inputFileName, outputFileName=None,
-                          confidenceThreshold=DEFAULT_CONFIDENCE_THRESHOLD,linewidth=2):
+                          confidenceThreshold=DEFAULT_CONFIDENCE_THRESHOLD,linewidth=DEFAULT_LINE_WIDTH):
     """
     Convenience wrapper to apply render_bounding_boxes to a single image
     """
@@ -209,6 +211,7 @@ def render_bounding_box(box, score, classLabel, inputFileName, outputFileName=No
     render_bounding_boxes(boxes,scores,[classLabel],[inputFileName],outputFileNames,
                           confidenceThreshold,linewidth)
 
+
 def render_bounding_boxes(boxes, scores, classes, inputFileNames, outputFileNames=[],
                           confidenceThreshold=DEFAULT_CONFIDENCE_THRESHOLD,linewidth=2):
     """
@@ -276,7 +279,8 @@ def render_bounding_boxes(boxes, scores, classes, inputFileNames, outputFileName
             # Origin is the upper-left
             iLeft = x
             iBottom = y
-            rect = patches.Rectangle((iLeft,iBottom),w,h,linewidth=linewidth,edgecolor='r',
+            boxColor = BOX_COLORS[int(classes[iImage][iBox]) % len(BOX_COLORS)]
+            rect = patches.Rectangle((iLeft,iBottom),w,h,linewidth=linewidth,edgecolor=boxColor,
                                      facecolor='none')
 
             # Add the patch to the Axes
@@ -304,7 +308,7 @@ def render_bounding_boxes(boxes, scores, classes, inputFileNames, outputFileName
 # ...def render_bounding_boxes
 
 
-def load_and_run_detector(modelFile, imageFileNames, 
+def load_and_run_detector(modelFile, imageFileNames, outputDir=None,
                           confidenceThreshold=DEFAULT_CONFIDENCE_THRESHOLD, detection_graph=None):
 
     if len(imageFileNames) == 0:        
@@ -323,12 +327,27 @@ def load_and_run_detector(modelFile, imageFileNames,
 
     assert len(boxes) == len(imageFileNames)
 
-    outputFileNames = []
+    outputFullPaths = []
+    outputFileNames = {}
+    if outputDir is not None:
+        os.makedirs(outputDir,exist_ok=True)
+        for iFn,fullInputPath in enumerate(imageFileNames):
+            fn = os.path.basename(fullInputPath).lower()
+
+            # Since we'll be writing a bunch of files to the same folder, rename
+            # as necessary to avoid collisions
+            if fn in outputFileNames:
+                nCollisions = outputFileNames[fn]
+                fn = str(nCollisions) + '_' + fn
+                outputFileNames[fn] = nCollisions + 1
+            else:
+                outputFileNames[fn] = 0
+            outputFullPaths.append(os.path.join(outputDir,fn))
 
     plt.ioff()
 
     render_bounding_boxes(boxes=boxes, scores=scores, classes=classes, 
-                          inputFileNames=imageFileNames, outputFileNames=outputFileNames,
+                          inputFileNames=imageFileNames, outputFileNames=outputFullPaths,
                           confidenceThreshold=confidenceThreshold)
 
     return detection_graph
@@ -353,7 +372,8 @@ def load_and_run_detector(modelFile, imageFileNames,
     imageFileNames = [r"D:\temp\test\1\NE2881-9_RCNX0195_xparent.png"]
 
     detection_graph = load_and_run_detector(modelFile,imageFileNames,
-                                            DEFAULT_CONFIDENCE_THRESHOLD,detection_graph)
+                                            confidenceThreshold=DEFAULT_CONFIDENCE_THRESHOLD,
+                                            detection_graph=detection_graph)
 
 
 #%% File helper functions
@@ -406,10 +426,19 @@ def main():
 
     parser = argparse.ArgumentParser()
     parser.add_argument('detectorFile', type=str)
-    parser.add_argument('--imageDir', action='store', type=str, default='', help='Directory to search for images, with optional recursion')
-    parser.add_argument('--imageFile', action='store', type=str, default='', help='Single file to process, mutually exclusive with imageDir')
-    parser.add_argument('--threshold', action='store', type=float, default=DEFAULT_CONFIDENCE_THRESHOLD, help='Confidence threshold, don''t render boxes below this confidence')
-    parser.add_argument('--recursive', action='store_true', help='Recurse into directories, only meaningful if using --imageDir')
+    parser.add_argument('--imageDir', action='store', type=str, default='', 
+                        help='Directory to search for images, with optional recursion')
+    parser.add_argument('--imageFile', action='store', type=str, default='', 
+                        help='Single file to process, mutually exclusive with imageDir')
+    parser.add_argument('--threshold', action='store', type=float, 
+                        default=DEFAULT_CONFIDENCE_THRESHOLD, 
+                        help='Confidence threshold, don''t render boxes below this confidence')
+    parser.add_argument('--recursive', action='store_true', 
+                        help='Recurse into directories, only meaningful if using --imageDir')
+    parser.add_argument('--forceCpu', action='store_true', 
+                        help='Force CPU detection, even if a GPU is available')
+    parser.add_argument('--outputDir', type=str, default=None, 
+                       help='Directory for output images (defaults to same as input)')
 
     if len(sys.argv[1:])==0:
         parser.print_help()
@@ -426,14 +455,18 @@ def main():
         imageFileNames = [args.imageFile]
     else:
         imageFileNames = findImages(args.imageDir,args.recursive)
-
+
+    if args.forceCpu:
+        os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
+        os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
     # Hack to avoid running on already-detected images
     imageFileNames = [x for x in imageFileNames if DETECTION_FILENAME_INSERT not in x]
 
     print('Running detector on {} images'.format(len(imageFileNames)))    
 
     load_and_run_detector(modelFile=args.detectorFile, imageFileNames=imageFileNames, 
-                          confidenceThreshold=args.threshold)
+                          confidenceThreshold=args.threshold, outputDir=args.outputDir)
 
 
 if __name__ == '__main__':